MAC Scheduling Strategies in LTE Advanced

An Efficient scheduling algorithm at the data link layer is needed in multiuser systems to efficiently exploit the benefits of multiuser multiple input multiple output (MIMO). The 3G partnership programme (3GPP) does not specify any specific scheduling for Long Term Evolution (LTE) Advanced; we can have any one of the scheduling strategies applicable for LTE Advanced. There is substantial amount of literature on scheduling algorithms for multiuser wireless systems. In this paper, we are presenting various types of scheduling schemes of LTE Advanced, their advantages, and inefficiencies.Keywords – Scheduling, MIMO, LTE Advanced, Channel state information (CSI) , Adaptive modulation and coding (AMC)

An intelligent fuzzy logic-based content and channel aware downlink scheduler for scalable video over OFDMA wireless systems

The recent advancements of wireless technology and applications make downlink scheduling and resource allocations an important research topic. In this paper, we consider the problem of downlink scheduling for multi-user scalable video streaming over OFDMA channels. The video streams are precoded using a scalable video coding (SVC) scheme. We propose a fuzzy logic-based scheduling algorithm, which prioritises the transmission to different users by considering video content, and channel conditions. Furthermore, a novel analytical model and a new performance metric have been developed for the performance analysis of the proposed scheduling algorithm. The obtained results show that the proposed algorithm outperforms the content-blind/channel aware scheduling algorithms with a gain of as much as 19% in terms of the number of supported users. The proposed algorithm allows for a fairer allocation of resources among users across the entire sector coverage, allowing for the enhancement of video quality at edges of the cell while minimising the degradation of users closer to the base station

Mechanisms for QoE optimisation of video traffic: a review paper

Transmission of video traffic over the Internet has grown exponentially in the past few years with no sign of waning. This increasing demand for video services has changed user expectation of quality. Various mechanisms have been proposed to optimise the Quality of Experience (QoE) of end users’ video. Studying these approaches are necessary for new methods to be proposed or combination of existing ones to be tailored. We discuss challenges facing the optimisation of QoE for video traffic in this paper. It surveys and classifies these mechanisms based on their functions. The limitation of each of them is identified and future directions are highlighted